1. Field
The present invention relates generally to automatic information capture techniques and, more particularly to the secondary publishing (or, abstracting and indexing) industry.
2. Background
Captioned components such as figures and tables represent the distilled essence of research communicated in academic articles. Although the marginalia surrounding these displays of data is useful, researchers are eager to view the actual data collected, observed, or modeled to determine the article's relevance to their work. Raw data sets are usually unavailable, but the processed data displayed in figures and tables are as, or even more, valuable.
The primary objective of a literature search is to find articles containing information most relevant to researchers' interests. Neither traditional article-level indexing provided by standard Abstracting & Indexing (A & I) services, nor full-text indexing whereby all text within a document is indexed, can restrict a result set to only those publications which contain data of interest.
For one reason, many key variables are excluded from traditional A&I searches because, although discretely important, they are generally not reflected in the more general nature of the author's abstract or the article title, traditional grist for the A&I indexing mill. Also, variables can be hidden from full-text searches because critical text within figures and tables is actually part of an image file which is not indexed (and made searchable) in full-text search systems. Web harvesters (e.g. Google) do not distil text from images. Furthermore, variables are ‘diluted’ in full-text indexes because many matches are peripheral; i.e., the variable of interest appears as an indirect reference (e.g. in a literature reference cited within an article). As a result, the identified article may not actually contain a figure or table including that particular variable.
A secondary objective of a literature search has been more intractable—and arguably more valuable. Any variable appearing in a figure or table within an article can be searched and linked to other studies examining the same variable. Traditional A&I services are adequate tools to help answer research questions, but there remains a need for indexing other information such as, for example, tables and figures that goes further. By revealing data links in studies across disciplines, new avenues of research can be illuminated.